مقالات رزومه دکتر علی محمدی

Low Noise Amplifier (LNA) is the first critical and important element in the designing of analog VLSI systems and wireless communications technology. In this paper, in order to establish an appropriate trade-off between the contradictory design objectives of an LNA circuit and the improvement of its efficiency and optimality indexes, a Computer-Aided Design (CAD) tool has been used based on the use of soft computing techniques including meta-heuristic intelligent optimization methods. For this purpose, the intelligent sizing of circuit elements and the auto-circuit design have been implemented by a new and effective Multi-Objective version of the Modified Inclined Planes System Optimization (MOMIPO) algorithm. Output results, compared with other studies, indicate a desirable achievement of design characteristics and constraints along with a variety of responses in the form of a Pareto Front. The execution of optimizer algorithm in the MATLAB environment and circuit simulations has been performed using the HSPICE software.

The proposed control scheme in this paper is based on the design of an optimal load distribution of reactive power for High-Voltage Direct-Current systems (HVDCs). The purpose is to monitor and implement appropriate operations to create a balance in the power and eliminate the voltage or current that has exceeded the permissible limit. Two-terminal HVDC transmission lines are of the most important elements of the power system. The optimization of reactive power distribution for power systems is defined based on the minimization of power loss under equal and unequal constraints. The problem of optimizing the reactive power distribution in integrated AC-DC power systems in the form of HVDC lines is generalized with regard to the control specifications for power transmission. In this paper, the problem is solved using Genetic Optimization Algorithm (GA). The validation, efficiency and the effectiveness of the proposed method are measured by comparing the results of the GA and those obtained by previous researches. Results indicate the effectiveness of the proposed method in the optimization of power distribution and the design of HVDC lines.

Low Noise Amplifier (LNA) is the first critical and important element in the designing of analog VLSI systems and wireless communications technology. In this paper, in order to establish an appropriate trade-off between the contradictory design objectives of an LNA circuit and the improvement of its efficiency and optimality indexes, a Computer-Aided Design (CAD) tool has been used based on the use of soft computing techniques including meta-heuristic intelligent optimization methods. For this purpose, the intelligent sizing of circuit elements and the auto-circuit design have been implemented by a new and effective Multi-Objective version of the Modified Inclined Planes System Optimization (MOMIPO) algorithm. Output results, compared with other studies, indicate a desirable achievement of design characteristics and constraints along with a variety of responses in the form of a Pareto Front. The execution of optimizer algorithm in the MATLAB environment and circuit simulations has been performed using the HSPICE software.

The proposed control scheme in this paper is based on the design of an optimal load distribution of reactive power for High-Voltage Direct-Current systems (HVDCs). The purpose is to monitor and implement appropriate operations to create a balance in the power and eliminate the voltage or current that has exceeded the permissible limit. Two-terminal HVDC transmission lines are of the most important elements of the power system. The optimization of reactive power distribution for power systems is defined based on the minimization of power loss under equal and unequal constraints. The problem of optimizing the reactive power distribution in integrated AC-DC power systems in the form of HVDC lines is generalized with regard to the control specifications for power transmission. In this paper, the problem is solved using Genetic Optimization Algorithm (GA). The validation, efficiency and the effectiveness of the proposed method are measured by comparing the results of the GA and those obtained by previous researches. Results indicate the effectiveness of the proposed method in the optimization of power distribution and the design of HVDC lines.

Low Noise Amplifier (LNA) is the first critical and important element in the designing of analog VLSI systems and wireless communications technology. In this paper, in order to establish an appropriate trade-off between the contradictory design objectives of an LNA circuit and the improvement of its efficiency and optimality indexes, a Computer-Aided Design (CAD) tool has been used based on the use of soft computing techniques including meta-heuristic intelligent optimization methods. For this purpose, the intelligent sizing of circuit elements and the auto-circuit design have been implemented by a new and effective Multi-Objective version of the Modified Inclined Planes System Optimization (MOMIPO) algorithm. Output results, compared with other studies, indicate a desirable achievement of design characteristics and constraints along with a variety of responses in the form of a Pareto Front. The execution of optimizer algorithm in the MATLAB environment and circuit simulations has been performed using the HSPICE software.

The proposed control scheme in this paper is based on the design of an optimal load distribution of reactive power for High-Voltage Direct-Current systems (HVDCs). The purpose is to monitor and implement appropriate operations to create a balance in the power and eliminate the voltage or current that has exceeded the permissible limit. Two-terminal HVDC transmission lines are of the most important elements of the power system. The optimization of reactive power distribution for power systems is defined based on the minimization of power loss under equal and unequal constraints. The problem of optimizing the reactive power distribution in integrated AC-DC power systems in the form of HVDC lines is generalized with regard to the control specifications for power transmission. In this paper, the problem is solved using Genetic Optimization Algorithm (GA). The validation, efficiency and the effectiveness of the proposed method are measured by comparing the results of the GA and those obtained by previous researches. Results indicate the effectiveness of the proposed method in the optimization of power distribution and the design of HVDC lines.

Intelligent optimization methods effectively explore and review the response space using past experiences a population of search agents. These population-based techniques can solve complex optimization problems with a defined number of iterations. This paper evaluates the performance of different types of common and powerful optimization algorithms in the system identification problem in order to optimal design and modeling of Infinite Impulse Response digital filters. Assumed methods include the Genetic Algorithm and Differential Evolution both based on evolutionary strategy along with six swarm intelligence algorithms, Particle Swarm Optimization, Gravitational Search Algorithm, Inclined Planes system Optimization, Ant Lion Optimizer, Teaching-Learning-Based Optimization, and, for the first time, Biogeography-Based Optimization. In the present study, the IIR system identification problem is assumed as a single-objective optimization function. It is evaluated for two experimental and challenging IIR models for the equivalent and reduced order modeling. To evaluate the efficiency and performance of the algorithms, the simulation results are evaluated in terms of Indicator of Success and Degree of Reliability with Mean Square Error. Also, the effect of reducing search agents on the performance of algorithms is analyzed. The overall estimation of the results confirms the acknowledgment of the effectiveness of the proposed evaluation indexes and the desirable performance of the proposed methods, especially for the PSO, IPO and BBO algorithms in terms of convergence characteristics, average runtime, average values of MSE, and IoS and DoR indices; GA and GSA algorithms in terms of convergence, runtime and DoR; DE method for running time; ALO algorithm for the mean of MSE, and TLBO algorithm in terms of the convergence characteristics, mean IoS, and DoR percent

The powerfulness and effectiveness of the optimization methods are motivations of the researchers to use them in complex engineering problems. In this paper, the performance of the three optimization algorithms based on swarm intelligence ( IPO, PSO) and evolutionary technique (GA) for calculation the channel's widths of the transistors were evaluated compared with each others. The fitness functions are defined in order to the better integration and to improve the power consumption and delay of Level Shifter circuit (LS) with changing the voltage level of 0.4 to 3 volts using 0.35-um CMOS technology .Simulation results for the sample circuit show that it reach a power consumption of 0.222pW and a delay value of 9.113ns with PSO algorithm, a power consumption of 0.39 nW and delay value of 3.741 ns with IPO algorithm, and values of 0.235 nW and 3.711 ns whit GA algorithm. In addition to a dramatic improvement in power and delay, minimum of channel's widths also were obtained. All implementations of paper were performed in MATLAB and HSPICE.